Academic Literature

Higher VET Earnings in UK – Early earnings differential associated with high-level vocational/technical education tends to disappear by the age of 30 study finds

Using rich administrative data for a full cohort of English secondary school leavers (2002/03 academic year), we compare earnings of people with higher vocational/technical qualifications to the earnings of degree holders at the age of 30, while controlling for prior attainment and background characteristics.

We find that by the age of 30 the early earnings differential associated with high-level vocational/technical education tends to disappear and degree holders earn more on average. However, there is strong heterogeneity by gender and subject area. There are especially high returns related to higher vocational/technical education in STEM subjects, which remain significantly above those of many degree holders several years after graduation.

Education investment is one of the major sources driving productivity and innovation in the economy. Successful higher education is particularly important as it also represents one of society’s key mechanisms to create social mobility and prosperity, especially for those from deprived families. It does this because of the significant earnings returns associated with high- level qualifications (e.g. see Belfield et al. (2018), and because of many other benefits to individuals (such as non-cognitive skills) and to the wider community.
Most of the micro-econometric research on the earnings effects and social mobility created by higher education focuses on honours degrees, i.e. Bachelor of Arts (BA) and Bachelor of Science (BSc) degrees, which represent the vast majority of higher education. However, there are also programmes of higher vocational and technical education, which are e.g. important for people with university-entry qualifications (“Level 3”) obtained in vocational programmes.

To date, there are no econometric studies of earnings benefits focused specifically on such “higher vocational and technical programmes” of tertiary education and how they compare to e.g. earnings of degree holders. This paper provides estimates for these programmes, using the new Longitudinal Education Outcomes (LEO) data, which link earnings from administrative data at census-level to individual records from England’s central education register covering education from primary schools all the way up to university.


We take a deep look into the value of qualifications of tertiary education in England, exploring differences in earnings profiles between higher vocational/technical and academic programmes. Higher vocational programmes last either for one year in tertiary education (“Level 4” qualifications) like Higher National Certificates (HNCs) and Level 4 National Vocational Qualifications (NVQs), or two years (“Level 5”), which include Higher National Diplomas (HNDs), Foundation Degrees, NVQs Level 5 and other qualifications. In contrast, academic programmes are predominantly bachelor’s degrees and a few other three years programmes like graduate certificates, graduate diplomas, etc. (“Level 6”).

We analyse rich administrative data for a cohort of English secondary school leavers, who are old enough for us to be able to estimate some medium-term differences in labour market outcomes when choosing between high-level vocational/technical or academic education. We focus on the cohort finishing compulsory education (age 16) in the summer of 2003 and look into their earnings by age 30, at time when most of them will have been in the labour market for several years. However, it may well be that differential returns of these qualifications change as the cohort ages.

Empirical research design

We estimate empirical earnings functions in the tradition of the Mincer (1974) human capital model using Ordinary Least Squares (OLS) and Inverse Probability Weighting Regression Adjustment (IPWRA), combined with the Least Absolute Shrinkage and Selection Operator (LASSO) that refines the most exhaustive specification. The rich set of covariates chosen by LASSO includes gender, work experience, ethnicity, Free School Meal (FSM) eligibility, region, Index of Multiple Deprivation at the Lower Layer Super Output Area level, GCSEs results, broad subject area, and school type.


In an initial descriptive analysis, we explore education progression and describe the highest level of education of individuals over time. This shows that higher level vocational/technical qualifications (Level 4-5) are the highest education achievement of very few people in the cohort (around 2%). While tertiary education attainment increases over time, Level 4-5 vocational qualifications tend to be acquired relatively late compared to degrees, which are mostly achieved by age 22/23 (i.e. until 2009 for this cohort). We also observe that students with Level 4-5 vocational qualifications have very diverse education backgrounds, ranging from Entry level to Level 3. This is very different to students aiming for degrees, who almost exclusively take A-Levels. Male and female students also make very different subject choices. Looking into their earnings over time, we find comparatively similar earnings trajectories for Level 4-5 students, which look very different from the earnings of those with Level 6 academic qualifications.

In the econometric analysis, we estimate whether earnings of achievers of Level 4-5 vocational/technical qualifications in 2017 differ from those having acquired degrees. We find that earnings for male degree holders are similar to higher vocational/technical education if they studied in non-Russell group universities, and higher for those from Russell group universities. Earnings for female degree holders are found to be higher regardless of the university type compared to those who achieved higher vocational/technical education. Within these overall findings, there is strong heterogeneity of effects by subject area and also by gender. When looking into results by subject, we find that earnings of males with Level 4- 5 Science, Technology, Engineering and Mathematics (“STEM”) qualifications are comparable or higher than earnings of STEM degree holders. Results for male students with qualifications in construction are similar, showing high returns for both academic and vocational qualifications. These empirical findings remain valid after controlling for prior attainment, and estimating human capital models with more sophisticated econometric techniques such as the IPWRA combined with LASSO method.

These findings are produced by carefully specified econometric models and estimated using rich observational data. However, estimates can only be interpreted as reflecting the causal effect of qualifications on earnings if all relevant characteristics influencing both are
captured within the model. This will not be true if omitted variables (such as non-cognitive skills) are important for influencing both earnings and choice of qualification path – and if they are not adequately captured by included controls (such as prior attainment). This is an important caveat to bear in mind when interpreting the results of this paper and all research using similar methodologies. The size of the data set has no bearing on this issue. Notwithstanding this important caveat, it is informative to compare the earnings differential to higher level vocational versus academic education using the biggest data set available to consider this issue in England.

Further research

In the next stage of this work, we will use several more recent cohorts of secondary school leavers in order to provide a comprehensive set of estimates of earnings differentials associated with the full range of higher education options (vocational compared to academic) compared to counterfactual Level 3 attainment. The use of multiple cohorts, which – given the small number of individuals studying for Level 4 and 5 qualifications – will be important in boosting the sample and improving the precision of our estimates. This will be particularly useful for a range of sub-group analyses. Also, we will be considering the implications of differential drop-out between individuals who pursue different routes.


Chosen excerpts by Job Market Monitor. Read the whole story at A comparison of earnings related to higher level vocational/technical and academic education


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